code: def metric_which_needs_x(
      solution, prediction, X_data, consider_col, val_threshold
  ):
      # custom function defining accuracy
      assert X_data is not None
      rel_idx = X_data[:, consider_col] > val_threshold
      return np.mean(solution[rel_idx] == prediction[rel_idx])
  
file_path: auto-sklearn/examples/40_advanced/example_metrics.py
imports: import numpy
  import sklearn.model_selection
  import sklearn.datasets
  import sklearn.metrics
  import autosklearn.classification
  import autosklearn.metrics
label_desc: Use image node_id 5 for calling a global function with example usage: metric_which_needs_x(solution, prediction, X_data, consider_col, val_threshold) and returns: np